Dear workshop community,
We will convene for the Applied Statistics Workshop (Gov 3009) next week on
Wednesday (2/6).
The speaker is* Maya Mathur *(Harvard Epidemiology) who will be presenting
her work "Sensitivity analysis for publication bias and selective reporting
in meta-analysis."
*Where:* CGIS Knafel Building, Room K354 (see this link
<https://map.harvard.edu/?bld=04471&level=9> for directions).
*When: *Wednesday, February 6th at 12 noon - 1:30 pm.
*Abstract:* We propose sensitivity analyses for selection in meta-analysis
due to publication bias, selective reporting, and "p-hacking". We consider
a publication process such that "statistically significant'' positive
results are more likely to be published than negative or "nonsignificant''
results by an unknown ratio. Using inverse-probability weighting and robust
estimation that accommodates non-normal true effects, small meta-analyses,
and clustering, we develop sensitivity analyses that enable statements such
as: "For publication bias to shift the observed point estimate to the null,
'significant' positive results would need to be at least 30-fold more
likely to be published than negative or 'nonsignificant' results.''
Comparable statements can be made regarding shifting to a chosen non-null
value or shifting the confidence interval. We show that a worst-case
meta-analytic point estimate under maximal publication bias can be obtained
simply by conducting a standard meta-analysis of only the negative and
"nonsignificant'' studies; this method sometimes indicates that no amount
of publication bias could "explain away'' the results. We illustrate the
proposed methods using real-life meta-analyses. An R package is
forthcoming.
*All are welcome! Lunch is provided! *
Best,
Connor Jerzak
Applied Statistics Workshop -- Graduate Student Coordinator
An anonymous feedback form for the workshop can be found here at this link
<https://docs.google.com/forms/d/e/1FAIpQLScp4lPVBtp4Akf6K6ggmfcTUSIUHEJX89-CU8HWrQPpe9pjTw/viewform?usp=sf_link>.
Workshop listserv sign-up at this link
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